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Generative AI and the Future of Pedagogical Sustainability: Balancing Creative Innovation with Ethical Fairness

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Education and Approaches".

Deadline for manuscript submissions: 31 March 2027 | Viewed by 714

Special Issue Editors

Prof. Dr. Despo Ktoridou

E-Mail Website
Guest Editor
Department of Management & MIS, University of Nicosia, 2417 Nicosia, Cyprus
Interests: ICT integration in the educational practice; technology and innovation management pedagogies; open and online distance learning practices
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nicholas Theodorakopoulos

E-Mail Website
Guest Editor
Department of Economics and Business, School of Economics, Business and Computer Science, Neapolis University Pafos, Paphos, Cyprus
Interests: ICT integration in learning & teaching; technology; innovation management and enterpeneurship; diversity and inclusion
Special Issues, Collections and Topics in MDPI journals
Dr. Vasso Stylianou

E-Mail Website
Guest Editor
Department of Computer Science, School of Sciences and Engineering, University of Nicosia, 2417 Nicosia, Cyprus
Interests: ICT integration in learning & teaching; knowledge management; human–computer interaction; creative thinking and learning; diversity, inclusion, and sustainability education and practice

Special Issue Information

Dear Colleagues,

This Special Issue welcomes research spanning higher education, executive education, professional training, continuing education, and lifelong learning, including business and management education and computing-related disciplines (Information Systems, MIS, Computer Science, Software Engineering, Data Science), emphasizing educator-led and trainer-led transformation.

This Special Issue addresses the sustainability of education in the GenAI era across higher education, executive education, professional training, continuing education, and lifelong learning in business and management education and computing-related disciplines (Information Systems, MIS, Computer Science, Software Engineering, Data Science). We define educational sustainability through four interconnected dimensions aligned with UN Sustainable Development Goals: (1) economic sustainability—long-term viability, cost-effectiveness, and learning transfer to professional workplaces; (2) social sustainability—equity, accessibility, inclusivity, and reducing digital divides across diverse global learner populations; (3) environmental sustainability—carbon footprint and energy consumption of AI-enhanced educational technologies and fostering environmental stewardship and climate literacy; (4) institutional sustainability—resilience, integrity, quality assurance, and adaptability of educational governance frameworks and assessment systems. Generative AI presents both opportunities and threats across these dimensions. While GenAI can democratize personalized learning and reduce educator workload, it risks exacerbating inequities through unequal access to premium tools, undermining academic integrity systems, consuming significant computational energy with environmental consequences, and disrupting established pedagogical models without clear evidence of long-term learning effectiveness. This Special Issue examines how educators and trainers can lead sustainable transformation—redesigning curricula, assessment practices, and institutional policies to harness GenAI's benefits while mitigating risks to equity, environmental responsibility, learning quality, and institutional resilience.

Topics

We invite conceptual, empirical, and practice-based research operationalizing sustainability through measurable indicators:

  1. Curriculum & Learning Outcomes: GenAI-era competency models; human-AI co-creativity for sustainability challenges; cognitive offloading impacts; sustainable development education; social equity simulations.
  2. Assessment & Academic Integrity: AI-resilient assessment design; sustainable integrity systems; micro-credentials and green skills certification; cost–benefit analysis of AI-enhanced assessment.
  3. Equity, Ethics & Inclusion: Algorithmic equity and bias; digital divide 2.0; accessibility and universal design; environmental footprint of AI-enhanced education; multilingual and cross-cultural learning.
  4. Institutional Governance & Faculty Development: Sustainable governance frameworks; faculty professional development; data privacy and security; green AI procurement; policy and regulatory sustainability; vendor lock-in and institutional autonomy.

Prof. Dr. Despo Ktoridou
Prof. Dr. Nicholas Theodorakopoulos
Dr. Vasso Stylianou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • generative AI (GenAI)
  • sustainable education
  • GenAI-enabled pedagogy
  • educational sustainability
  • professional learning
  • executive education
  • sustainable assessment design
  • AI-authentic assessment
  • educational equity
  • social sustainability in education
  • academic integrity systems
  • AI governance
  • learning transfer
  • green AI
  • environmental footprint of EdTech
  • human–AI co-creativity
  • cognitive offloading
  • digital divide 2.0
  • algorithmic fairness
  • institutional resilience
  • SDG 4 quality education
  • educational resource efficiency
  • faculty professional development
  • EdTech carbon accounting

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

24 pages, 4590 KB  
Article
The AI Use Gap: Visibility Management of Generative AI Use in Higher Education in the Peruvian Andes
by Saríah Fanny Oré Gálvez, Cecilia Choque Pomasunco, Alex Foyams Molina Linares, Walter Victor Castro Aponte, Solón Dante Carhuallanqui Ibarra, Rubén Ñaupari Molina, Juan Carlos Terres León, Olga Karina Durand De La O, Crispin H. W. Barnes and Luis De Los Santos Valladares
Sustainability 2026, 18(12), 5923; https://doi.org/10.3390/su18125923 (registering DOI) - 10 Jun 2026
Abstract
The study examines discrepancies between personally reported and declared use of generative artificial intelligence (GenAI) among university students from a public university located in the Peruvian Andes, operationalized as the AI Use Gap, an exploratory discrepancy indicator based on two self-reported measures. Drawing [...] Read more.
The study examines discrepancies between personally reported and declared use of generative artificial intelligence (GenAI) among university students from a public university located in the Peruvian Andes, operationalized as the AI Use Gap, an exploratory discrepancy indicator based on two self-reported measures. Drawing on a sequential explanatory mixed-methods design, the study combines survey data (N = 150), experimental vignette evaluations, and qualitative follow-up interviews to explore how students manage the visibility and disclosure of AI use in academic contexts. Findings indicate relatively high levels of AI use alongside a consistent discrepancy between personally reported and declared use, suggesting patterns of differential reporting across contexts. Quantitative analyses did not show clearly differentiated exploratory relational patterns between the AI Use Gap and the psychosocial/contextual indicators examined, including perceived stigma, concealment, normative ambiguity, and peer pressure. Given the exploratory nature and limited internal consistency of the contextual indicators, these findings were interpreted cautiously as provisional exploratory patterns rather than as evidence of stable psychosocial relationships. Qualitative findings suggest that AI disclosure practices are shaped by socially evaluative and context-dependent processes, including fear of judgment, uncertainty regarding acceptable AI use, and selective disclosure strategies. Participants frequently described AI use as widespread but not consistently disclosed across academic settings. Overall, the findings suggest that discrepancies between AI use and disclosure may be better understood as forms of visibility management shaped by institutional ambiguity and social expectations rather than by stable individual-level characteristics alone. Rather than validating stable psychosocial mechanisms, the study explores an emerging and context-sensitive phenomenon using provisional contextual indicators intended to capture heterogeneous patterns of perception and disclosure. The study contributes to ongoing discussions regarding transparency, academic integrity, and the social regulation of AI use in higher education, particularly in under-researched Global South contexts. Full article
(This article belongs to the Special Issue Generative AI and the Future of Pedagogical Sustainability: Balancing Creative Innovation with Ethical Fairness)
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15 pages, 711 KB  
Article
Socio-Emotional Competencies for Educational Sustainability in Diverse Territorial Contexts: Emotional Metaknowledge in Secondary School Students in Chile
by Yasna Anabalón Anabalón and Adriana Sanhueza Cisterna
Sustainability 2026, 18(11), 5574; https://doi.org/10.3390/su18115574 - 1 Jun 2026
Viewed by 282
Abstract
Socio-emotional competencies are increasingly recognized as a relevant dimension of educational sustainability because they are theoretically and empirically linked to student well-being, school coexistence, participation, and the development of more inclusive educational communities. This article examines self-perceived emotional metaknowledge in 181 first-year secondary [...] Read more.
Socio-emotional competencies are increasingly recognized as a relevant dimension of educational sustainability because they are theoretically and empirically linked to student well-being, school coexistence, participation, and the development of more inclusive educational communities. This article examines self-perceived emotional metaknowledge in 181 first-year secondary school students from two Chilean schools located in contrasting territorial contexts: Santiago and Quillón, Ñuble Region. The TMMS-24 was used to assess three dimensions: Emotional Attention, Emotional Clarity, and Emotional Repair. After data cleaning, 181 valid cases were analyzed. Given the repeated-measures structure of the data, a mixed ANOVA was conducted, with emotional dimension as the within-subject factor and locality as the between-subject factor. Reliability analyses, assumption checks, effect sizes, confidence intervals, and Holm-adjusted post hoc comparisons were also included. The results showed no significant main effect of locality, suggesting that the overall level of self-perceived emotional metaknowledge did not differ significantly between Santiago and Quillón. However, a significant main effect of emotional dimension and a significant dimension × locality interaction were found. Emotional Repair obtained the highest scores in the total sample, while Santiago showed significantly higher Emotional Attention than Quillón. These findings suggest that emotional metaknowledge should be interpreted as a multidimensional construct, with specific differences across emotional dimensions rather than broad territorial contrasts. From the perspective of SDG 4, the study suggests the relevance of socio-emotional learning approaches that are context-sensitive, territorially aware, and oriented toward quality, equity, inclusion, and school coexistence. Full article
(This article belongs to the Special Issue Generative AI and the Future of Pedagogical Sustainability: Balancing Creative Innovation with Ethical Fairness)
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